The primary emphasis of this project is to develop and validate a highly automated, clinically feasible system for accurate qualitative (morphology) and quantitative (volumetry) assessment of the heart by 3 dimensional echocardiography (3DE). The specific hypothesis of this research is; 3DE images of the human heart can provide more accurate qualitative and quantitative information than current 2-dimensional echocardiography. The aims are to test the hypothesis in the following areas: 1) Image Acquisition; Using a transesophageal approach and acquisition in two cylindrical geometries (pyramidal and conical), find optimal number of incremental scans required for detailed morphological studies and for accurate left ventricular (LV) volume evaluation. 2) Image Segmentation: Develop a two step algorithm for LV extraction in 3DE. The first step includes automated identification of the LV cavity and determination of a global threshold suitable for initial segmentation of the LV and cardiac structures. In the second step, an advanced algorithm for cavity boundary detection is used to create a 3D computer representation of the LV chamber. The algorithm simulates autonomous growth of a natural cell which adapts its shape to the surroundings. The software controlled growth and elastic properties of the "cell membrane" should reproduce the spatial distribution of the LV endocardial surface. The resulting 3D object will be used for qualitative and quantitative evaluation of the LV. 3) Clinical Validation and Application: Accuracy of LV volumetry by 3DE will be validated through the comparison of this method to volumetry by computed tomography. Patients with normal and symmetrically or asymmetrically enlarged LV will be selected. The validated 3DE algorithm will be subsequently applied to studies in patients with ischemic, valvular and congenital heart diseases examined in the Clinical Echocardiographic Laboratory. The significance of the project is that comprehensible 3DE images of cardiac anatomy and accurate LV volumetry will improve the quality of the diagnosis, treatment, and follow-up of patients with cardiovascular diseases.